Availability and Affordability of Kidney Health Laboratory Tests around the Globe
Bibliographic record
Abstract
BACKGROUND: Kidney disease is a major global public health problem, and laboratory testing of kidney health measures is essential for diagnosis and monitoring. The availability and affordability of kidney health laboratory tests across countries has not been systematically described. METHODS: The International Society of Nephrology (ISN), in partnership with leaders of a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference, surveyed a representative subset of ISN-Global Kidney Health Atlas (ISN-GKHA) respondents from April to June 2020. We assessed the association between country gross national income (GNI) per capita and laboratory testing availability and affordability. RESULTS: Of 33 regional expert nephrologists invited, 24 (73%) responded, representing all 10 ISN regions around the world. Availability of kidney health laboratory tests was as follows: serum Cr (100%), serum cystatin C (67%), urine albumin (96%), urine Cr (100%), and dipstick urinalysis (100%). Median (IQR) reimbursement values in international dollars were as follows: serum Cr Int$ 6.61 (3.42-8.84), serum cystatin C Int$ 31.51 (17.36-46.25), urine albumin Int$ 10.22 (5.90-15.42), urine Cr Int$ 7.50 (1.66-8.84), and dipstick urinalysis Int$ 6.26 (2.56-8.40). Reimbursement values did not differ significantly by World Bank income group or by GNI per capita. CONCLUSION: There was widespread availability of kidney health laboratory tests and substantial variation in reimbursement values. To achieve meaningful progress across nations in mitigating the growth of kidney disease, access to affordable diagnostic technology is essential. Our results are highly relevant to policymakers and researchers as countries increasingly consider national strategies for kidney disease detection and management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".